Continuous Glucose Monitoring in Healthy Adults-Possible Applications in Health Care, Wellness, and Sports

Roman Holzer, Wilhelm Bloch, Christian Brinkmann, Roman Holzer, Wilhelm Bloch, Christian Brinkmann

Abstract

Introduction: Continuous glucose monitoring (CGM) systems were primarily developed for patients with diabetes mellitus. However, these systems are increasingly being used by individuals who do not have diabetes mellitus. This mini review describes possible applications of CGM systems in healthy adults in health care, wellness, and sports.

Results: CGM systems can be used for early detection of abnormal glucose regulation. Learning from CGM data how the intake of foods with different glycemic loads and physical activity affect glucose responses can be helpful in improving nutritional and/or physical activity behavior. Furthermore, states of stress that affect glucose dynamics could be made visible. Physical performance and/or regeneration can be improved as CGM systems can provide information on glucose values and dynamics that may help optimize nutritional strategies pre-, during, and post-exercise.

Conclusions: CGM has a high potential for health benefits and self-optimization. More scientific studies are needed to improve the interpretation of CGM data. The interaction with other wearables and combined data collection and analysis in one single device would contribute to developing more precise recommendations for users.

Keywords: CGM; application; continuous glucose monitoring; health care; healthy adults; lifestyle; nutrition; physical activity; sports; wearable.

Conflict of interest statement

C.B. is a member of the Abbott Advisory Board. All other authors declare that they have no conflict of interest.

Figures

Figure 1
Figure 1
Overview of different potential continuous glucose monitoring (CGM) applications in healthy adults.

References

    1. Heinemann L., Deiss D., Siegmund T., Schlüter S., Naudorf M., Sengbusch S.V., Lange K., Freckmann G. Glucose Measurement and Control in Patients with Type 1 or Type 2 Diabetes. Exp. Clin. Endocrinol. Diabetes. 2019;127:S8–S26. doi: 10.1055/a-1018-9090.
    1. Clarke S.F., Foster J.R. A History of Blood Glucose Meters and Their Role in Self-Monitoring of Diabetes Mellitus. Br. J. Biomed. Sci. 2012;69:83–93. doi: 10.1080/09674845.2012.12002443.
    1. Villena Gonzales W., Mobashsher A.T., Abbosh A. The Progress of Glucose Monitoring—A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors. Sensors. 2019;19:800. doi: 10.3390/s19040800.
    1. Benjamin E.M. Self-Monitoring of Blood Glucose: The Basics. Clin. Diabetes. 2002;20:45–47. doi: 10.2337/diaclin.20.1.45.
    1. American Diabetes Association 7. Diabetes Technology: Standards of Medical Care in Diabetes—2019. Diabetes Care. 2019;42:71–80. doi: 10.2337/dc19-S007.
    1. Heinemann L. Finger Pricking and Pain: A Never Ending Story. J. Diabetes Sci. Technol. 2008;2:919–921. doi: 10.1177/193229680800200526.
    1. Olczuk D., Priefer R. A History of Continuous Glucose Monitors (CGMs) in Self-Monitoring of Diabetes Mellitus. Diabetes Metab. Syndr. Clin. Res. Rev. 2018;12:181–187. doi: 10.1016/j.dsx.2017.09.005.
    1. Fogh-Andersen N., Altura B.M., Altura B.T., Siggaard-Andersen O. Composition of Interstitial Fluid. Clin. Chem. 1995;41:1522–1525. doi: 10.1093/clinchem/41.10.1522.
    1. Schrangl P., Reiterer F., Heinemann L., Freckmann G., Del Re L. Limits to the Evaluation of the Accuracy of Continuous Glucose Monitoring Systems by Clinical Trials. Biosensors. 2018;8:50. doi: 10.3390/bios8020050.
    1. Coyle S., Curto V.F., Benito-Lopez F., Florea L., Diamond D. Chapter 2.1—Wearable Bio and Chemical Sensors. In: Sazonov E., Neuman M.R., editors. Wearable Sensors. Academic Press; Oxford, UK: 2014. pp. 65–83.
    1. Richter E.A., Hargreaves M. Exercise, GLUT4, and Skeletal Muscle Glucose Uptake. Physiol. Rev. 2013;93:993–1017. doi: 10.1152/physrev.00038.2012.
    1. Staal O.M., Hansen H.M.U., Christiansen S.C., Fougner A.L., Carlsen S.M., Stavdahl Ø. Differences Between Flash Glucose Monitor and Fingerprick Measurements. Biosensors. 2018;8:93. doi: 10.3390/bios8040093.
    1. Schmelzeisen-Redeker G., Schoemaker M., Kirchsteiger H., Freckmann G., Heinemann L., del Re L. Time Delay of CGM Sensors: Relevance, Causes, and Countermeasures. J. Diabetes Sci. Technol. 2015;9:1006–1015. doi: 10.1177/1932296815590154.
    1. Davey R.J., Low C., Jones T.W., Fournier P.A. Contribution of an Intrinsic Lag of Continuous Glucose Monitoring Systems to Differences in Measured and Actual Glucose Concentrations Changing at Variable Rates in Vitro. J. Diabetes Sci. Technol. 2010;4:1393–1399. doi: 10.1177/193229681000400614.
    1. Joseph J.I. Review of the Long-Term Implantable Senseonics Continuous Glucose Monitoring System and Other Continuous Glucose Monitoring Systems. J. Diabetes Sci. Technol. 2021;15:167–173. doi: 10.1177/1932296820911919.
    1. Holzer R., Bloch W., Brinkmann C. Minimally Invasive Electrochemical Patch-Based Sensor System for Monitoring Glucose and Lactate in the Human Body—A Survey-Based Analysis of the End-User’s Perspective. Sensors. 2020;20:5761. doi: 10.3390/s20205761.
    1. Klonoff D.C., Ahn D., Drincic A. Continuous Glucose Monitoring: A Review of the Technology and Clinical Use. Diabetes Res. Clin. Pract. 2017;133:178–192. doi: 10.1016/j.diabres.2017.08.005.
    1. Reiterer F., Polterauer P., Schoemaker M., Schmelzeisen-Redecker G., Freckmann G., Heinemann L., del Re L. Significance and Reliability of MARD for the Accuracy of CGM Systems. J. Diabetes Sci. Technol. 2017;11:59–67. doi: 10.1177/1932296816662047.
    1. Heinemann L., Schoemaker M., Schmelzeisen-Redecker G., Hinzmann R., Kassab A., Freckmann G., Reiterer F., Del Re L. Benefits and Limitations of MARD as a Performance Parameter for Continuous Glucose Monitoring in the Interstitial Space. J. Diabetes Sci. Technol. 2020;14:135–150. doi: 10.1177/1932296819855670.
    1. Freckmann G., Link M., Kamecke U., Haug C., Baumgartner B., Weitgasser R. Performance and Usability of Three Systems for Continuous Glucose Monitoring in Direct Comparison. J. Diabetes Sci. Technol. 2019;13:890–898. doi: 10.1177/1932296819826965.
    1. Alva S., Bailey T., Brazg R., Budiman E.S., Castorino K., Christiansen M.P., Forlenza G., Kipnes M., Liljenquist D.R., Liu H. Accuracy of a 14-Day Factory-Calibrated Continuous Glucose Monitoring System With Advanced Algorithm in Pediatric and Adult Population With Diabetes. J. Diabetes Sci. Technol. 2022;16:70–77. doi: 10.1177/1932296820958754.
    1. Boscari F., Galasso S., Facchinetti A., Marescotti M.C., Vallone V., Amato A.M.L., Avogaro A., Bruttomesso D. FreeStyle Libre and Dexcom G4 Platinum Sensors: Accuracy Comparisons during Two Weeks of Home Use and Use during Experimentally Induced Glucose Excursions. Nutr. Metab. Cardiovasc. Dis. 2018;28:180–186. doi: 10.1016/j.numecd.2017.10.023.
    1. Welsh J.B., Gao P., Derdzinski M., Puhr S., Johnson T.K., Walker T.C., Graham C. Accuracy, Utilization, and Effectiveness Comparisons of Different Continuous Glucose Monitoring Systems. Diabetes Technol. Ther. 2019;21:128–132. doi: 10.1089/dia.2018.0374.
    1. Freckmann G., Pleus S., Link M., Baumstark A., Schmid C., Högel J., Haug C. Accuracy Evaluation of Four Blood Glucose Monitoring Systems in Unaltered Blood Samples in the Low Glycemic Range and Blood Samples in the Concentration Range Defined by ISO 15197. Diabetes Technol. Ther. 2015;17:625–634. doi: 10.1089/dia.2015.0043.
    1. Aleppo G., Webb K. Continuous Glucose Monitoring in Clinical Practice: A Stepped Guide to Data Review and Interpretation. J. Diabetes Sci. Technol. 2019;13:664–673. doi: 10.1177/1932296818813581.
    1. Scheiner G. CGM Retrospective Data Analysis. Diabetes Technol. Ther. 2016;18((Suppl. 2)):14–22. doi: 10.1089/dia.2015.0281.
    1. Shah V.N., DuBose S.N., Li Z., Beck R.W., Peters A.L., Weinstock R.S., Kruger D., Tansey M., Sparling D., Woerner S., et al. Continuous Glucose Monitoring Profiles in Healthy Nondiabetic Participants: A Multicenter Prospective Study. J. Clin. Endocrinol. Metab. 2019;104:4356–4364. doi: 10.1210/jc.2018-02763.
    1. Battelino T., Danne T., Bergenstal R.M., Amiel S.A., Beck R., Biester T., Bosi E., Buckingham B.A., Cefalu W.T., Close K.L., et al. Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range. Diabetes Care. 2019;42:1593–1603. doi: 10.2337/dci19-0028.
    1. Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group Variation of Interstitial Glucose Measurements Assessed by Continuous Glucose Monitors in Healthy, Nondiabetic Individuals. Diabetes Care. 2010;33:1297–1299. doi: 10.2337/dc09-1971.
    1. Borg R., Kuenen J.C., Carstensen B., Zheng H., Nathan D.M., Heine R.J., Nerup J., Borch-Johnsen K., Witte D.R., on behalf of the ADAG Study Group Real-Life Glycaemic Profiles in Non-Diabetic Individuals with Low Fasting Glucose and Normal HbA1c: The A1C-Derived Average Glucose (ADAG) Study. Diabetologia. 2010;53:1608–1611. doi: 10.1007/s00125-010-1741-9.
    1. Hall H., Perelman D., Breschi A., Limcaoco P., Kellogg R., McLaughlin T., Snyder M. Glucotypes Reveal New Patterns of Glucose Dysregulation. PLoS Biol. 2018;16:e2005143. doi: 10.1371/journal.pbio.2005143.
    1. Klimontov V.V., Saik O.V., Korbut A.I. Glucose Variability: How Does It Work? Int. J. Mol. Sci. 2021;22:7783. doi: 10.3390/ijms22157783.
    1. Rani V., Deep G., Singh R.K., Palle K., Yadav U.C.S. Oxidative Stress and Metabolic Disorders: Pathogenesis and Therapeutic Strategies. Life Sci. 2016;148:183–193. doi: 10.1016/j.lfs.2016.02.002.
    1. Chan C.L., Pyle L., Newnes L., Nadeau K.J., Zeitler P.S., Kelsey M.M. Continuous Glucose Monitoring and Its Relationship to Hemoglobin A1c and Oral Glucose Tolerance Testing in Obese and Prediabetic Youth. J. Clin. Endocrinol. Metab. 2015;100:902–910. doi: 10.1210/jc.2014-3612.
    1. Acciaroli G., Sparacino G., Hakaste L., Facchinetti A., Di Nunzio G.M., Palombit A., Tuomi T., Gabriel R., Aranda J., Vega S., et al. Diabetes and Prediabetes Classification Using Glycemic Variability Indices From Continuous Glucose Monitoring Data. J. Diabetes Sci. Technol. 2018;12:105–113. doi: 10.1177/1932296817710478.
    1. Ringeval M., Wagner G., Denford J., Paré G., Kitsiou S. Fitbit-Based Interventions for Healthy Lifestyle Outcomes: Systematic Review and Meta-Analysis. J. Med. Internet Res. 2020;22:e23954. doi: 10.2196/23954.
    1. Wong S.H., Tan Z.Y.A., Cheng L.J., Lau S.T. Wearable Technology-Delivered Lifestyle Intervention amongst Adults with Overweight and Obese: A Systematic Review and Meta-Regression. Int. J. Nurs. Stud. 2021;18:104163. doi: 10.1016/j.ijnurstu.2021.104163.
    1. Jo A., Coronel B.D., Coakes C.E., Mainous A.G. Is There a Benefit to Patients Using Wearable Devices Such as Fitbit or Health Apps on Mobiles? A Systematic Review. Am. J. Med. 2019;132:1394–1400.e1. doi: 10.1016/j.amjmed.2019.06.018.
    1. Tong H.L., Quiroz J.C., Kocaballi A.B., Fat S.C.M., Dao K.P., Gehringer H., Chow C.K., Laranjo L. Personalized Mobile Technologies for Lifestyle Behavior Change: A Systematic Review, Meta-Analysis, and Meta-Regression. Prev. Med. 2021;148:106532. doi: 10.1016/j.ypmed.2021.106532.
    1. Wright E.E., Subramanian S. Evolving Use of Continuous Glucose Monitoring Beyond Intensive Insulin Treatment. Diabetes Technol. Ther. 2021;23:S-12–S-18. doi: 10.1089/dia.2021.0191.
    1. Ehrhardt N., Al Zaghal E. Behavior Modification in Prediabetes and Diabetes: Potential Use of Real-Time Continuous Glucose Monitoring. J. Diabetes Sci. Technol. 2018;13:271–275. doi: 10.1177/1932296818790994.
    1. Fechner E., Op ’t Eyndt C., Mulder T., Mensink R.P. Diet-Induced Differences in Estimated Plasma Glucose Concentrations in Healthy, Non-Diabetic Adults Are Detected by Continuous Glucose Monitoring—A Randomized Crossover Trial. Nutr. Res. 2020;80:36–43. doi: 10.1016/j.nutres.2020.06.001.
    1. Dehghani Zahedani A., Shariat Torbaghan S., Rahili S., Karlin K., Scilley D., Thakkar R., Saberi M., Hashemi N., Perelman D., Aghaeepour N., et al. Improvement in Glucose Regulation Using a Digital Tracker and Continuous Glucose Monitoring in Healthy Adults and Those with Type 2 Diabetes. Diabetes Ther. 2021;12:1871–1886. doi: 10.1007/s13300-021-01081-3.
    1. Mattes R.D., Friedman M.I. Hunger. DDI. 1993;11:65–77. doi: 10.1159/000171402.
    1. Ciampolini M., Lovell-Smith H.D., Kenealy T., Bianchi R. Hunger Can Be Taught: Hunger Recognition Regulates Eating and Improves Energy Balance. Int. J. Gen. Med. 2013;6:465–478. doi: 10.2147/IJGM.S40655.
    1. Jospe M.R., de Bruin W.E., Haszard J.J., Mann J.I., Brunton M., Taylor R.W. Teaching People to Eat According to Appetite—Does the Method of Glucose Measurement Matter? Appetite. 2020;151:104691. doi: 10.1016/j.appet.2020.104691.
    1. Diaz K.M., Shimbo D. Physical Activity and the Prevention of Hypertension. Curr. Hypertens. Rep. 2013;15:659–668. doi: 10.1007/s11906-013-0386-8.
    1. Lee I.-M. Physical Activity and Cancer Prevention--Data from Epidemiologic Studies. Med. Sci. Sports Exerc. 2003;35:1823–1827. doi: 10.1249/01.MSS.0000093620.27893.23.
    1. Mammen G., Faulkner G. Physical Activity and the Prevention of Depression: A Systematic Review of Prospective Studies. Am. J. Prev. Med. 2013;45:649–657. doi: 10.1016/j.amepre.2013.08.001.
    1. Montesi L., Moscatiello S., Malavolti M., Marzocchi R., Marchesini G. Physical Activity for the Prevention and Treatment of Metabolic Disorders. Intern. Emerg. Med. 2013;8:655–666. doi: 10.1007/s11739-013-0953-7.
    1. Nunan D., Mahtani K.R., Roberts N., Heneghan C. Physical Activity for the Prevention and Treatment of Major Chronic Disease: An Overview of Systematic Reviews. Syst. Rev. 2013;2:56. doi: 10.1186/2046-4053-2-56.
    1. Wannamethee S.G., Shaper A.G. Physical Activity in the Prevention of Cardiovascular Disease. Sports Med. 2001;31:101–114. doi: 10.2165/00007256-200131020-00003.
    1. Sparks J.R., Kishman E.E., Sarzynski M.A., Davis J.M., Grandjean P.W., Durstine J.L., Wang X. Glycemic Variability: Importance, Relationship with Physical Activity, and the Influence of Exercise. Sports Med. Health Sci. 2021;3:183–193. doi: 10.1016/j.smhs.2021.09.004.
    1. Solomon T.P.J., Eves F.F., Laye M.J. Targeting Postprandial Hyperglycemia With Physical Activity May Reduce Cardiovascular Disease Risk. But What Should We Do, and When Is the Right Time to Move? Front. Cardiovasc. Med. 2018;5:99. doi: 10.3389/fcvm.2018.00099.
    1. Bellini A., Nicolò A., Bulzomì R., Bazzucchi I., Sacchetti M. The Effect of Different Postprandial Exercise Types on Glucose Response to Breakfast in Individuals with Type 2 Diabetes. Nutrients. 2021;13:1440. doi: 10.3390/nu13051440.
    1. Holzer R., Schulte-Körne B., Seidler J., Predel H.-G., Brinkmann C. Effects of Acute Resistance Exercise with and without Whole-Body Electromyostimulation and Endurance Exercise on the Postprandial Glucose Regulation in Patients with Type 2 Diabetes Mellitus: A Randomized Crossover Study. Nutrients. 2021;13:4322. doi: 10.3390/nu13124322.
    1. Little J.P., Jung M.E., Wright A.E., Wright W., Manders R.J.F. Effects of High-Intensity Interval Exercise versus Continuous Moderate-Intensity Exercise on Postprandial Glycemic Control Assessed by Continuous Glucose Monitoring in Obese Adults. Interval Train. 2014;01:835–841. doi: 10.1139/apnm-2013-0512.
    1. Borror A., Zieff G., Battaglini C., Stoner L. The Effects of Postprandial Exercise on Glucose Control in Individuals with Type 2 Diabetes: A Systematic Review. Sports Med. 2018;48:1479–1491. doi: 10.1007/s40279-018-0864-x.
    1. Aqeel M., Forster A., Richards E.A., Hennessy E., McGowan B., Bhadra A., Guo J., Gelfand S., Delp E., Eicher-Miller H.A. The Effect of Timing of Exercise and Eating on Postprandial Response in Adults: A Systematic Review. Nutrients. 2020;12:221. doi: 10.3390/nu12010221.
    1. Bailey K.J., Little J.P., Jung M.E. Self-Monitoring Using Continuous Glucose Monitors with Real-Time Feedback Improves Exercise Adherence in Individuals with Impaired Blood Glucose: A Pilot Study. Diabetes Technol. Ther. 2016;18:185–193. doi: 10.1089/dia.2015.0285.
    1. Liao Y., Basen-Engquist K.M., Urbauer D.L., Bevers T.B., Hawk E., Schembre S.M. Using Continuous Glucose Monitoring to Motivate Physical Activity in Overweight and Obese Adults: A Pilot Study. Cancer Epidemiol. Prev. Biomark. 2020;29:761–768. doi: 10.1158/1055-9965.EPI-19-0906.
    1. Liao Y., Schembre S. Acceptability of Continuous Glucose Monitoring in Free-Living Healthy Individuals: Implications for the Use of Wearable Biosensors in Diet and Physical Activity Research. JMIR Mhealth Uhealth. 2018;6:e11181. doi: 10.2196/11181.
    1. Tank A.W., Lee Wong D. Peripheral and Central Effects of Circulating Catecholamines. Compr. Physiol. 2015;5:1–15. doi: 10.1002/cphy.c140007.
    1. Di Dalmazi G., Pagotto U., Pasquali R., Vicennati V. Glucocorticoids and Type 2 Diabetes: From Physiology to Pathology. J. Nutr. Metab. 2012;2012:525093. doi: 10.1155/2012/525093.
    1. Rohleder N. Stress and Inflammation—The Need to Address the Gap in the Transition between Acute and Chronic Stress Effects. Psychoneuroendocrinology. 2019;105:164–171. doi: 10.1016/j.psyneuen.2019.02.021.
    1. Zea M., Bellagambi F.G., Ben Halima H., Zine N., Jaffrezic-Renault N., Villa R., Gabriel G., Errachid A. Electrochemical Sensors for Cortisol Detections: Almost There. TrAC Trends Anal. Chem. 2020;132:116058. doi: 10.1016/j.trac.2020.116058.
    1. Adesida Y., Papi E., McGregor A.H. Exploring the Role of Wearable Technology in Sport Kinematics and Kinetics: A Systematic Review. Sensors. 2019;19:1597. doi: 10.3390/s19071597.
    1. Lutz J., Memmert D., Raabe D., Dornberger R., Donath L. Wearables for Integrative Performance and Tactic Analyses: Opportunities, Challenges, and Future Directions. Int. J. Environ. Res. Public Health. 2020;17:59. doi: 10.3390/ijerph17010059.
    1. Düking P., Stammel C., Sperlich B., Sutehall S., Muniz-Pardos B., Lima G., Kilduff L., Keramitsoglou I., Li G., Pigozzi F., et al. Necessary Steps to Accelerate the Integration of Wearable Sensors Into Recreation and Competitive Sports. Curr. Sports Med. Rep. 2018;17:178–182. doi: 10.1249/JSR.0000000000000495.
    1. Rothschild J.A., Kilding A.E., Plews D.J. What Should I Eat before Exercise? Pre-Exercise Nutrition and the Response to Endurance Exercise: Current Prospective and Future Directions. Nutrients. 2020;12:3473. doi: 10.3390/nu12113473.
    1. Arent S.M., Cintineo H.P., McFadden B.A., Chandler A.J., Arent M.A. Nutrient Timing: A Garage Door of Opportunity? Nutrients. 2020;12:1948. doi: 10.3390/nu12071948.
    1. Kloby Nielsen L.L., Tandrup Lambert M.N., Jeppesen P.B. The Effect of Ingesting Carbohydrate and Proteins on Athletic Performance: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Nutrients. 2020;12:1483. doi: 10.3390/nu12051483.
    1. Moore D.R. Nutrition to Support Recovery from Endurance Exercise: Optimal Carbohydrate and Protein Replacement. Curr. Sports Med. Rep. 2015;14:294–300. doi: 10.1249/JSR.0000000000000180.
    1. Ravindra P.V., Janhavi P., Divyashree S., Muthukumar S.P. Nutritional Interventions for Improving the Endurance Performance in Athletes. Arch. Physiol. Biochem. 2020;30:1–8. doi: 10.1080/13813455.2020.1733025.
    1. Ormsbee M.J., Bach C.W., Baur D.A. Pre-Exercise Nutrition: The Role of Macronutrients, Modified Starches and Supplements on Metabolism and Endurance Performance. Nutrients. 2014;6:1782–1808. doi: 10.3390/nu6051782.
    1. Jeukendrup A.E., Killer S.C. The Myths Surrounding Pre-Exercise Carbohydrate Feeding. ANM. 2010;57:18–25. doi: 10.1159/000322698.
    1. Brun J.F., Dumortier M., Fedou C., Mercier J. Exercise Hypoglycemia in Nondiabetic Subjects. Diabetes Metab. 2001;27:92–106.
    1. Yang W.-H., Park H., Grau M., Heine O. Decreased Blood Glucose and Lactate: Is a Useful Indicator of Recovery Ability in Athletes? Int. J. Environ. Res. Public Health. 2020;17:5470. doi: 10.3390/ijerph17155470.
    1. Evans P.L., McMillin S.L., Weyrauch L.A., Witczak C.A. Regulation of Skeletal Muscle Glucose Transport and Glucose Metabolism by Exercise Training. Nutrients. 2019;11:2432. doi: 10.3390/nu11102432.
    1. Jensen T.E., Richter E.A. Regulation of Glucose and Glycogen Metabolism during and after Exercise. J. Physiol. 2012;590:1069–1076. doi: 10.1113/jphysiol.2011.224972.
    1. Ishihara K., Uchiyama N., Kizaki S., Mori E., Nonaka T., Oneda H. Application of Continuous Glucose Monitoring for Assessment of Individual Carbohydrate Requirement during Ultramarathon Race. Nutrients. 2020;12:1121. doi: 10.3390/nu12041121.
    1. Oishi A., Makita N., Kishi S., Isogawa A., Iiri T. Continuous Glucose Monitoring of a Runner during Five Marathons. Sci. Sports. 2018;33:370–374. doi: 10.1016/j.scispo.2018.05.001.
    1. Kulawiec D.G., Zhou T., Knopp J.L., Chase J.G. Continuous Glucose Monitoring to Measure Metabolic Impact and Recovery in Sub-Elite Endurance Athletes. Biomed. Signal Processing Control. 2021;70:103059. doi: 10.1016/j.bspc.2021.103059.
    1. Cano A., Ventura L., Martinez G., Cugusi L., Caria M., Deriu F., Manca A. Analysis of Sex-Based Differences in Energy Substrate Utilization during Moderate-Intensity Aerobic Exercise. Eur. J. Appl. Physiol. 2022;122:29–70. doi: 10.1007/s00421-021-04802-5.
    1. Varlamov O., Bethea C.L., Roberts C.T. Sex-Specific Differences in Lipid and Glucose Metabolism. Front. Endocrinol. 2015;5:241. doi: 10.3389/fendo.2014.00241.
    1. Wismann J., Willoughby D. Gender Differences in Carbohydrate Metabolism and Carbohydrate Loading. J. Int. Soc. Sports Nutr. 2006;3:28. doi: 10.1186/1550-2783-3-1-28.
    1. Magkos F., Wang X., Mittendorfer B. Metabolic Actions of Insulin in Men and Women. Nutrition. 2010;26:686–693. doi: 10.1016/j.nut.2009.10.013.
    1. Horton T.J., Grunwald G.K., Lavely J., Donahoo W.T. Glucose Kinetics Differ between Women and Men, during and after Exercise. J. Appl. Physiol. 2006;100:1883–1894. doi: 10.1152/japplphysiol.01431.2005.
    1. Bellazzi R., Dagliati A., Sacchi L., Segagni D. Big Data Technologies: New Opportunities for Diabetes Management. J. Diabetes Sci. Technol. 2015;9:1119–1125. doi: 10.1177/1932296815583505.
    1. Rigla M., García-Sáez G., Pons B., Hernando M.E. Artificial Intelligence Methodologies and Their Application to Diabetes. J. Diabetes Sci. Technol. 2018;12:303–310. doi: 10.1177/1932296817710475.
    1. Kavakiotis I., Tsave O., Salifoglou A., Maglaveras N., Vlahavas I., Chouvarda I. Machine Learning and Data Mining Methods in Diabetes Research. Comput. Struct. Biotechnol. J. 2017;15:104–116. doi: 10.1016/j.csbj.2016.12.005.
    1. Contreras I., Vehi J. Artificial Intelligence for Diabetes Management and Decision Support: Literature Review. J. Med. Internet Res. 2018;20:e10775. doi: 10.2196/10775.
    1. Bandodkar A.J., Jeerapan I., Wang J. Wearable Chemical Sensors: Present Challenges and Future Prospects. ACS Sens. 2016;1:464–482. doi: 10.1021/acssensors.6b00250.
    1. Kim J., Campbell A.S., Wang J. Wearable Non-Invasive Epidermal Glucose Sensors: A Review. Talanta. 2018;177:163–170. doi: 10.1016/j.talanta.2017.08.077.
    1. Yang Y., Gao W. Wearable and Flexible Electronics for Continuous Molecular Monitoring. Chem. Soc. Rev. 2019;48:1465–1491. doi: 10.1039/C7CS00730B.
    1. Jernelv I.L., Milenko K., Fuglerud S.S., Hjelme D.R., Ellingsen R., Aksnes A. A Review of Optical Methods for Continuous Glucose Monitoring. Appl. Spectrosc. Rev. 2019;54:543–572. doi: 10.1080/05704928.2018.1486324.
    1. Shokrekhodaei M., Quinones S. Review of Non-Invasive Glucose Sensing Techniques: Optical, Electrical and Breath Acetone. Sensors. 2020;20:1251. doi: 10.3390/s20051251.
    1. Ye S., Feng S., Huang L., Bian S. Recent Progress in Wearable Biosensors: From Healthcare Monitoring to Sports Analytics. Biosensors. 2020;10:205. doi: 10.3390/bios10120205.
    1. Gao B., He Z., He B., Gu Z. Wearable Eye Health Monitoring Sensors Based on Peacock Tail-Inspired Inverse Opal Carbon. Sens. Actuators B Chem. 2019;288:734–741. doi: 10.1016/j.snb.2019.03.029.

Source: PubMed

3
Předplatit